39 results about "Atmospheric models" patented technology

The invention discloses a wind speed forecasting system based on deep learning, and belongs to the technical field of weather forecasting. The system comprises a coupled mode framework which integrates a triple nested architecture of an atmospheric mode WRF, an ocean mode ROMS and a sea wave mode SWAN, and transmits variables through a model coupling tool MCT; the deep learning roughness parameterization module is integrated in an MYNN boundary layer scheme of the atmospheric mode WRF and calculates the sea surface roughness in real time; the full-wave spectrum integration module is embedded into the ocean mode ROMS, receives wave spectrum data provided by the ocean mode SWAN and calculates a Stokes drift profile; and the intelligent correction module is used for carrying out spatial interpolation on the wind speed data output by the mode, correcting errors by combining a LightGBM model, and outputting a final forecast product. According to the method, the deep neural network is embedded into the WRF boundary layer model kernel, the sea surface roughness parameter is updated in real time, the wave evolution process is dynamically responded, and the space-time adaptive capacity of wind field forecasting under the complex sea condition is remarkably improved.

The invention discloses a marine atmosphere prediction method, system and equipment considering a dynamic wave boundary layer and a medium. The method comprises the following steps: acquiring terrain and water depth elevation data of a sea area; establishing calculation boundary conditions and parameters of WRF atmospheric mode simulation and SWAN sea wave mode simulation; recording a spatial position wind speed vector perpendicular to the observation point in the WRF atmospheric mode simulation process and wave height time history data of the observation point in the SWAN sea wave mode simulation process; planning a calculation drainage basin of micro-scale drainage basin large vortex simulation, and setting resolutions of flow direction and spanwise grids; a bottom surface grid of a calculation drainage basin of micro-scale drainage basin large vortex simulation dynamically changes according to wave height time history data monitored by observation points on the basis of a spring dynamic grid technology; a spatial position wind speed vector of an observation point is assigned to a calculation basin entrance boundary of micro-scale basin large vortex simulation, and a micro-scale ocean atmospheric boundary layer is obtained by solving an incompressible Navier Stokes equation. The method improves the prediction efficiency and precision of the flow characteristics of the marine atmospheric boundary layer.

The invention discloses a floating object track prediction and tracing method and system based on WRF and HYSPLIT models, and relates to the technical field of power system power transmission line operation and maintenance, and the method comprises five units: a data acquisition unit, a three-dimensional atmosphere model construction unit, a floating object track prediction unit, a floating object tracing unit and a result display unit. The data acquisition unit acquires meteorological data and floating object information. The three-dimensional atmosphere model construction unit constructs an applicable three-dimensional atmosphere model on the basis of a WRF weather forecast mode. The floater trajectory prediction unit predicts the future trajectory of the floater through an HYSPLIT mixed single-particle Lagrange comprehensive trajectory model in combination with weather forecast data. The floating object traceability unit inverts the historical motion trail and source of the floating object. And the result display unit displays the floating object track prediction and traceability result based on a geographic information system. According to the method, the safety and reliability of the power transmission line are improved, accidents such as line hanging and tripping of the floaters are reduced, and accurate trajectory prediction and source inversion of the floaters are realized.

The invention discloses an atmospheric visibility and photovoltaic power forecasting method and device and a storage medium, and belongs to the field of photoelectric new energy, new-generation information technology and atmospheric environment, and the method comprises the steps: constructing an aerosol cluster model with fractal geometric characteristics based on a diffusion limitation condensation algorithm; calculating fractal dimensions of the aerosol cluster model by using a box counting method; according to the fractal dimension, calculating the optical equivalent radius of the aerosol cluster model of the fractal geometric features; coupling the optical equivalent radius into a mesoscale air quality mode, and calculating to obtain an atmospheric extinction coefficient considering the aerosol process; the atmospheric visibility and photovoltaic power forecast result is calculated by considering the atmospheric extinction coefficient of the aerosol process; according to the method, the physical simulation degree and the forecast simulation precision of the atmospheric aerosol optical characteristics by the atmospheric mode are improved, so that the simulation result of the mesoscale air quality mode on the atmospheric visibility and the photovoltaic power is remarkably improved.

The invention discloses an aviation radiation dose global distribution real-time calculation system based on ground detection equipment, which belongs to the technical field of radiation detection and comprises a ground radiation detection module, a dose simulation module and a data correction module. The ground radiation detection module is used for continuously collecting ionizing radiation data of an atmospheric bottom layer in a calm state and a solar high-energy particle event so as to improve data precision and a signal-to-noise ratio under a weak dose, and the dose simulation module receives latitude and longitude, height and time parameters of an aviation flight path, and calculates a standard atmospheric model and a cosmic ray energy spectrum in combination with the standard atmospheric model and the cosmic ray energy spectrum. The data processing module is used for calculating theoretical dose rates and particle type distribution of different height levels based on a Monte Carlo method and outputting the theoretical dose rates and the particle type distribution, and the data correction module is used for dynamically correcting parameters and weights of simulation results by combining measured data based on a deep learning algorithm of deep learning, so that adaptive fusion of the simulation data and the measured data is realized; and the ground radiation detection module comprises a semiconductor radiation detector, a data acquisition and preprocessing unit, a remote control module and a network communication module. The system has the characteristics of high real-time performance and wide coverage range.

The invention discloses a GNSS occultation open-loop forecasting method based on a cubic spline interpolation algorithm, and relates to the field of occultation open-loop forecasting. The method comprises the following steps: judging whether a current navigational star is atmospheric occultation or not through an occultation event forecasting algorithm; acquiring position and speed information of atmospheric occultation and a low earth orbit; carrying out occultation forecast calculation on atmospheric occultation by adopting an atmospheric model to obtain model Doppler caused by satellite motion and model pseudo-range caused by neutral atmosphere; the method comprises the following steps: caching n-second model Doppler, model pseudo-range and open-loop forecast time of occultation in a 1HZ task, and obtaining interpolation parameters of the model Doppler and the model pseudo-range by using cubic spline interpolation; through the interpolation parameters, carrying out interpolation to obtain a 100HZ model Doppler and a 100HZ model pseudo-range; through the model pseudo-range, signal emission time is obtained through calculation; through signal emission time of a 100HZ task period, a signal emission time deviation value is obtained through calculation and converted into a hardware adjustment count, and the hardware adjustment count is transmitted into FGPA adjustment so as to carry out open-loop tracking of atmospheric occultation.

The invention relates to the technical field of atmospheric parameter inversion models, provides an atmospheric model construction method and system based on virtual temperature correction, and solves the problem of insufficient dynamic scene adaptability. The method comprises the following steps: acquiring a radiation brightness observation value of a satellite thermal infrared band, synchronously recording a satellite observation zenith angle and an azimuth angle, and collecting earth surface coverage type data, dew point temperature and corresponding height information; and uplink and downlink radiation components are eliminated. A normalized vegetation coverage index is calculated based on satellite red light and near-infrared band reflectivity data, a specific emissivity mapping relation is constructed in combination with a land surface coverage type, and land surface specific emissivity space distribution is inverted. And generating vertical stratified atmosphere data based on the dew point temperature and height, and constructing radiation transmission path correction parameters in combination with the observation angle. And finally, establishing an atmospheric radiation transmission model, and outputting a continuous spatialization virtual temperature field. According to the method, the problem of insufficient dynamic scene adaptability in the prior art is solved, and high-precision inversion of the atmosphere deficiency temperature vertical section is realized.

The invention discloses an infrared simulation method and system based on a neural network and GPU parallel computing, and belongs to the field of infrared simulation. Fitting an all-weather atmospheric transmittance and a radiation value received by the earth surface by using an atmospheric model; preprocessing the infrared simulation data, and calculating a patch shielding probability value and a patch temperature value in a simulation scene by using a distributed GPU parallel framework; wherein the number of sampling points is dynamically adjusted through an adaptive patch sampling method in combination with the geometric area and complexity of a patch so as to calculate a patch shielding probability value, and the patch shielding probability value is introduced when a patch temperature value is calculated; and optimizing the surface patch temperature value to obtain a surface patch steady-state temperature value, calculating the radiation brightness of a specified wave band according to the surface patch steady-state temperature value, and finally rendering to obtain an infrared simulation image of a specified view angle under the specified wave band. The method solves the problems that in the prior art, radiation value and temperature field calculation is complex, shielding calculation efficiency is low, heat conduction simulation capacity is insufficient, and self-adaptive sampling is not fine enough.

The invention belongs to the technical field of electric power meteorology, and provides a medium and long term wind and light resource prediction method and system considering climate remote correlation factors, and the method comprises the steps: obtaining global climate index historical data, and carrying out the standardization processing of the data, and obtaining a standardized climate index; for the historical resource sequence of the target station, calculating the mutual information value of the standardized climate index, and constructing a forecasting factor set by taking the lag time corresponding to the maximum value of the mutual information as the optimal early warning window period; extracting wind and light resource measured data of the same period in historical years to construct a reference probability density function; and taking the reference probability density function as prior distribution, combining a preset dynamic mode prediction result as a likelihood function, and outputting a prediction result containing a deterministic value and a confidence interval. By means of the characteristic that ocean signals change slowly, the method breaks through the 15-day prediction limit of an atmospheric mode, effective trend prediction from the quarterly level to the annual level is successfully achieved, and the requirement for medium and long term resource evaluation is met.

The embodiment of the invention provides an atmospheric modeling coefficient determination method and device, electronic equipment and a storage medium. The method comprises the following steps: determining a plurality of candidate baselines and atmospheric modeling coefficients according to coordinate values and observation values of a reference station and ephemeris of a common-view satellite, and determining modeling residuals of the plurality of candidate baselines based on the atmospheric modeling coefficients; determining whether the atmospheric modeling coefficient meets a preset condition or not; if the preset condition is not met, determining a target baseline in the plurality of candidate baselines based on the modeling residual error, removing the target baseline, and updating a plurality of auxiliary reference stations included in the reference station network by adopting auxiliary reference stations corresponding to the remaining candidate baselines, returning to continuously execute the step of determining the plurality of candidate baselines and the atmospheric modeling coefficients according to the coordinate values and the observation values of the reference stations in the reference station network and the ephemeris of the common-view satellite; and if a preset condition is met, taking the atmosphere modeling coefficient as a target atmosphere modeling coefficient. The method is used for achieving the effect of improving the accuracy and reliability of the atmospheric modeling coefficient.

The invention belongs to the field of advection atmospheric mode algorithm development, and discloses a shape-preserving advection unified calculation method and system suitable for any polygon mesh, and the method comprises the following steps: carrying out the mesh division of a calculation domain of a standard example in an advection equation algorithm; standardized grid topology information is constructed for the grid units of the computational domain; initializing a standard example in the algorithm of the advection equation; and performing discretization solution on the advection equation through standardized grid topology information to complete shape-preserving advection unified calculation. According to the method, a general advection solution with calculation precision and stability can be provided for a complex grid numerical model in the fields of atmosphere simulation, ocean circulation and the like, and the development period of an atmosphere advection mode can be remarkably shortened.

The present invention discloses a GNSS occultation open-loop prediction method based on a cubic spline interpolation algorithm, and relates to the field of occultation open-loop prediction. The method comprises: determining whether the current navigation satellite is atmospheric occulted using an occultation event prediction algorithm; obtaining position and velocity information of the atmospheric occultation and the low Earth orbit; performing occultation prediction calculations on the atmospheric occultation using an atmospheric model to obtain a model Doppler caused by satellite motion and a model pseudorange caused by a neutral atmosphere; obtaining interpolation parameters of the model Doppler and model pseudorange by caching n seconds of model Doppler, model pseudorange, and open-loop prediction time of the occultation in a 1 Hz mission using cubic spline interpolation; obtaining the 100 Hz model Doppler and model pseudorange by interpolation using the interpolation parameters; and calculating the signal transmission time using the model pseudorange; calculating the signal transmission time deviation value using the signal transmission time of the 100 Hz mission cycle, and converting the calculated signal transmission time deviation value into a hardware adjustment count for input into the FGPA adjustment, thereby performing open-loop tracking of the atmospheric occultation.

The invention discloses a method for judging spatial atmospheric density, which is specifically implemented according to the following steps: a user provides input parameters, which are recorded as in; in is normalized; a constant term 1 is added to the parameter sequence after normalization operation; a neural network input layer weight matrix is ​​multiplied by the input sequence, and the number of calculations of the neural network hidden layer is n=1; a constant term 1 is added to the input sequence, so that a(n)=[a(n);1], so that the transformed input parameter sequence a(n) is multiplied by LW(n), a(n)=LW(n)*a(n), and a hidden layer calculation is completed; step 6, n=n+1, if n>3, the hidden layer calculation is completed, and the next step is entered; otherwise, n=n+1 is set, and the previous step is repeated to complete the next hidden layer calculation; the output layer is calculated; the calculation result is reversely normalized to obtain the spatial atmospheric density, and the spatial atmospheric density judgment is completed. The atmospheric judgment accuracy of the traditional atmospheric model in the spatial range can be improved.

The invention relates to the technical field of data processing, and discloses a horizontal grid registration and parallel computing method and system in climate mode coupling. The method comprises the following steps: performing registration processing on an atmospheric mode component through a component identity verification algorithm to obtain a mode component identifier; analyzing the horizontal grid geometric parameters according to the mode component identifier to obtain a grid basic information set; constructing masked and maskless horizontal grid configurations based on the grid basic information set; performing parallel domain decomposition processing on the dual grid configuration to obtain a parallel decomposition mapping table; establishing a global and local grid index bidirectional mapping relationship; and performing time step synchronization registration based on the bidirectional mapping relation to obtain a coupling validity verification result. The technical problem that a self-adaptive grid registration and parallel decomposition processing mechanism for air-sea coupling special requirements is lacked in an existing climate mode coupling technology is solved.

The present disclosure is directed to systems and methods enabling federated learning of atmospheric models for satellite-based navigation, via crowdsourcing training data. One method includes, causing, at a computing device, a determination of an error metric based on a difference between a set of measured values and a set of expected values. The set of expected values is based on an atmospheric model and a geolocation. The set of measured values is based on a set of satellite signals received at the computing device from a set of satellites. The error metric may be for the atmospheric model. The method further includes causing a transmission of a data structure from the computing device to an atmospheric model service. The transmitted data structure encodes the error metric (e.g., training data). The atmospheric modeling service employs Bayesian inference and the error metric as a conditional probability to refine the atmospheric model.

The application discloses a complex terrain processing method and system suitable for a three-dimensional non-hydrostatic atmospheric model, which comprises the following steps: adopting preset regional terrain data and an atmospheric background field, and performing atmospheric model preprocessing on the terrain data; performing key grid identification on the preset region to obtain a grid distribution, marking terrain nearby grid points according to the grid distribution and recording distance and slope information, obtaining a marked grid distribution, dividing the marked grid distribution according to a process number and calculating a sub-region, and performing adaptive grid encryption on the sub-region; updating a forecast variable value at a next moment by updating an atmospheric equation group of the sub-region after high-order numerical discretization, generating a logarithmic velocity profile based on the Monin-Obukhov similarity theory, processing an atmospheric velocity of a boundary layer according to the logarithmic velocity profile to obtain an ideal velocity distribution curve, and outputting atmospheric motion characteristics under a complex terrain by correcting a forecast variable on a grid point near a lower surface boundary.

The application discloses a digital-twin spatial channel continuous variable quantum key distribution method, and relates to the technical field of quantum information processing.The method comprises the following steps: constructing a satellite-ground station link model between a satellite and a ground station according to satellite orbit parameter data and ground station position information, and calculating satellite-ground station link dynamic parameters; constructing an atmospheric model based on the satellite-ground station link dynamic parameters and atmospheric parameters to simulate link attenuation loss at different times under a single orbit in the satellite-ground station link; simulating quantum state preparation process to adjust quantum state parameters and combining the link attenuation loss to calculate key generation rate to distribute satellite-ground station quantum keys.The dynamic model constructed based on satellite orbit parameters and ground station positions can calculate satellite-ground station link dynamic parameters in real time, and can establish an atmospheric model to quantify link attenuation and background noise under different weather conditions, adjust quantum state preparation parameters, and maximize key generation rate under the premise of ensuring security.

The present invention discloses a load calculation system for coastal port pile foundation structures based on a coupling mode, comprising: a hydrodynamic module, which evaluates the load and mechanical properties of the port pile foundation structure under different environmental conditions; the hydrodynamic module at least includes an atmospheric mode module, a wave mode module, an ocean mode module and a coupler module; wherein the coupler module exchanges and synchronizes data between the atmospheric mode module, the wave mode module and the ocean mode module; a data conversion module, which converts wind field data, wave field data and flow field data obtained by the hydrodynamic module into aerodynamic and hydrodynamic input files of the pile foundation structure; and a finite element analysis module, which receives the aerodynamic and hydrodynamic input files, establishes a port pile foundation structure model, and calculates the stress distribution and displacement response of the pile foundation structure, wherein the simulation results output include but are not limited to the stress cloud map, displacement field distribution and buckling phenomenon of the pile foundation.

This invention relates to a unified geometric calibration method for large-scale spaceborne SAR images, comprising: collecting SAR image products and preprocessing them to obtain intensity data; constructing an RD geometric positioning model based on SAR image auxiliary files; acquiring the corresponding orthophoto and digital elevation model of the SAR image, generating a database of control points and checkpoints, thereby calculating the geometric positioning deviation of the initial RD model; determining the sources of ground geometric positioning errors based on the SAR imaging mechanism, thereby establishing error equations and a geometric calibration model; obtaining atmospheric parameters using a standard atmospheric model and combining it with the Saas-Tamonin and Krobuscher models to achieve near-real-time estimation of atmospheric path delay; calculating SAR satellite imaging error correction parameters based on the control point database and the geometric calibration model, and then updating the RD geometric positioning model. Compared with existing technologies, the unified geometric calibration method for large-scale spaceborne SAR images adopted in this invention does not require the support of a geometric calibration field and does not rely on reanalysis meteorological products, thus possessing better versatility.

The invention discloses a communication channel intelligent prediction method and device under atmospheric disturbance, and relates to the technical field of communication, and the method comprises the steps: obtaining the atmospheric feature data and corresponding height information between a satellite and a ground end, determining the atmospheric disturbance data of the corresponding height based on the atmospheric feature data and the height information, and carrying out the intelligent prediction of a communication channel based on the height information. The method comprises the following steps: generating a prediction scale, fusing the prediction scale with atmospheric disturbance data, generating an atmospheric stratification model, determining a communication channel interval between a satellite and a ground end, determining a corresponding channel interval atmospheric model in the atmospheric stratification model according to the communication channel interval, generating an atmospheric change trend based on the prediction scale and the channel interval atmospheric model, and enabling the communication channel parameters to act on an atmospheric change trend, generating a channel quality change curve, and determining a quality prediction result of the communication channel based on the prediction scale and the channel quality change curve. Through the above mode, the problem of real-time prediction of the communication channel performance in a complex atmospheric environment is solved.

The application discloses a kind of sea-air wave flow coupling optimization method based on multiscale process, to solve the adaptability of existing coupling mode in multiscale process, physical description accuracy deviation and numerical conservation stability difference and other problems.This method first improves the physical parameterization: in atmospheric model, introduce the sea surface roughness parameterization based on wave spectrum dynamic correction, in ocean model, adopt dynamic bottom friction with energy conservation constraint.At the same time, the collaborative mechanism is used: creatively, multiscale adaptive coupling dispatcher is unified with high-order non-oscillatory conservation mapping algorithm and energy spectrum conservation mapping algorithm.The closed-loop collaborative mechanism forces to use flux mapping instead of field interpolation, ensures that the transfer of momentum, mass and energy remains strictly conserved under dynamic variable-frequency coupling, overcomes the numerical conservation barrier in variable-frequency coupling, significantly improves the simulation accuracy and long-term stability under extreme conditions such as typhoon.

The high-performance computing method of CALPUFF is realized based on workflow, which relates to the fields of atmospheric environment and computer processing technology. It solves the problems that the existing meteorological models have poor processing capabilities for abnormal situations, cannot support concurrency in calculations, have low computing efficiency, and are insufficient in analyzing and processing calculation results; and cannot support calculations for complex situations of multiple models, and can only solve single problems with a single script. The present invention is implemented based on an atmospheric model computing service system. According to the workflow model, a computing task is divided into multiple task nodes, which are completed one by one. This method integrates complex data, data analysis and processing, and realizes cloud service sharing. The atmospheric model computing service system of the present invention adopts a numerical simulation method to analyze the causes of atmospheric pollution under different climatic conditions and at different times within the range of the numerical model, and to identify the contribution rates of various pollution sources, various types of pollution sources, and each grid pollution source that affect atmospheric pollution, providing a decision-making support system for atmospheric pollution prevention and control.

The present invention relates to an image color correction method, electronic equipment and storage medium. The image color correction method comprises: obtaining the quantization level, image shooting time and position of the space-based remote sensing image according to the historical space-based remote sensing image, and constructing a corresponding relationship model of the corresponding time and position; obtaining the atmospheric absorption and ground object color composition according to the historical space-based remote sensing image, and constructing a color correction model; after obtaining a new space-based remote sensing image, the space-based remote sensing image is corrected by using the corresponding relationship model and the color correction model in sequence. The present invention can avoid the problem of randomness of color correction caused by the uncertainty of the atmospheric macroscopic scale and the local microscopic scale, and does not need to consider the complex settings in the atmospheric model. It is easy to use, and the operator does not need to have professional knowledge of the atmospheric model, which is conducive to the color restoration of the image.

The invention relates to a method for simulating a global UMLT area wind field and temperature and a 0-30 km wind field, and relates to the technical field of atmosphere remote sensing, and the method comprises the steps: transmitting 372 nm laser to the earth atmosphere through a satellite-borne laser radar system; calculating the number of echo photons generated by the resonance fluorescence effect of the received iron atoms based on the number density of the iron atoms in the WACCM atmospheric model and the temperature and pressure data in the ERA5 reanalysis data; and calculating the global atmospheric temperature and the global atmospheric wind speed of the UMLT region and the global atmospheric wind speed of 0-30km based on the echo photon number. According to the method, a WACCM atmospheric mode and ERA5 reanalysis data are used for simulating the satellite-borne ferro-laser radar to detect the global atmospheric wind speed and temperature and calculate corresponding errors, atmospheric parameters of the global scale are applied, obvious seasonal and regional characteristics are displayed, a more accurate method is provided for satellite-borne laser radar simulation, and the satellite-borne ferro-laser radar simulation method can be applied to simulation of the satellite-borne ferro-laser radar. And a more comprehensive simulation result can be obtained.

The disclosure relates to systems and methods for implementing joint learning of atmospheric models for satellite-based navigation via crowdsourcing training data. A method includes causing, at a computing device, a determination of an error metric based on a difference between a set of measurements and a set of desired values. The set of desired values is based on an atmospheric model and geolocation. The set of measurements is based on a set of satellite signals received at the computing device from a set of satellites. The error metric may be directed to the atmospheric model. The method further includes causing transmission of the data structure from the computing device to the atmospheric model service. The transmitted data structure encodes the error metric (e.g., training data). The atmospheric modeling service employs Bayesian inference and the error metric as conditional probabilities to refine the atmospheric model.

The invention discloses a digital twin space channel continuous variable quantum key distribution method, and relates to the technical field of quantum information processing, and the method comprises the steps: constructing a satellite-ground link model between a satellite and a ground station according to satellite orbit parameter data and ground receiving station position information, and calculating satellite-ground link dynamic parameters; based on the satellite-ground link dynamic parameters and the atmospheric parameters, constructing an atmospheric model to simulate link attenuation loss at different moments under a single orbit in a satellite-ground link; and simulating a quantum state preparation process to adjust quantum state parameters, and calculating a key generation rate in combination with the link attenuation loss to distribute satellite-ground quantum keys. According to the method, a dynamic model is constructed based on satellite orbit parameters and ground station positions, dynamic parameters of a satellite-ground link can be calculated in real time, an atmosphere model is established to quantify link attenuation and background noise under different weather conditions, quantum state preparation parameters are adjusted, and the key generation rate is maximized on the premise that safety is guaranteed.

The present invention discloses an efficient atmospheric model physical process task division method, comprising the following steps: S1, obtaining the supernode number of each process in the atmospheric model; S2, grouping each process in the atmospheric model according to the supernode number information obtained in S1, and dividing the processes with the same supernode number into the same group; S3, first-level task division, using the same grid division method as the power framework, ensuring that the atmospheric model power framework and the physical process in the same group of processes have the same grid; S4, second-level task division, adjusting the grid division between processes in the group in the atmospheric model physical process, and redistributing the grid to the processes in the group. The present invention can not only make the atmospheric model physical process calculation tasks relatively balanced, but also reduce the communication overhead when the atmospheric model is coupled with the power framework, and can significantly improve the overall performance of the atmospheric model during large-scale parallelization.

The invention relates to a wind resource assessment technology, discloses an atmospheric mode wind resource assessment method supporting visual parameter configuration, and solves the problems that in current wind resource assessment, the process is split, the data management efficiency is low, and result display and application are disjointed, so that efficient and accurate assessment requirements are difficult to meet. According to the scheme, the method comprises the steps that firstly, calculation parameters input by a user are obtained through a front-end visual interface, and a mode configuration file which can be directly used for atmospheric mode calling is generated; thirdly, calling an atmospheric mode based on the mode configuration file to execute numerical simulation, and generating meteorological element data containing wind speed and wind direction in combination with the preprocessed external reanalysis data; then, converting the meteorological element data from a potential height coordinate to a terrain height coordinate, and generating a map file and a time sequence file; and finally, according to the atlas file and the time sequence file, in a front-end visual interface, displaying a meteorological element atlas and a time sequence chart in the visual interface.

The invention discloses an iron resonance fluorescence laser radar temperature and wind speed inversion error analysis method, and belongs to the technical field of low ionosphere detection. According to the iron resonance fluorescence laser radar temperature and wind speed inversion error analysis method, an iron resonance fluorescence laser radar simulation model is constructed, and photon echo signals are simulated in combination with an NRLMSIS-00 atmosphere model and actually measured iron atom density data; analyzing the influence of laser frequency jitter and light quantum noise on the inversion precision by adopting a Monte Carlo method; then, the error performance of a frequency scanning method and the error performance of a three-frequency ratio method are compared, it is proved that the error of the frequency scanning method in temperature inversion is lower, and the iron resonance fluorescence laser radar temperature and wind speed inversion error analysis method can provide guidance for systematic error modeling and parameter design of an iron resonance fluorescence laser radar; and the accuracy of atmospheric temperature and wind speed inversion can be improved.